NDA Help Center

Collection - General Tab

Fields available for edit on the top portion of the page include:

  • Collection Title
  • Investigators
  • Collection Description
  • Collection Phase
  • Funding Source
  • Clinical Trials

Collection Status: The visibility status of an NDA Collection.  Collection Status can be Shared or Private.  Collections in Shared status are visible to all users and can be searched in the NDA Query Tool. Private Collections are not visible to NDA users.  The Status of an NDA Collection only affects the visibility of information about the Collection (metadata) and does not relate to the status of the record-level research data in the NDA Collection.

Collection Phase: The current status of a research project submitting data to an NDA Collection, based on the timing of the award and/or the data that have been submitted.
 

  • Pre-Enrollment: The default entry made when the NDA Collection is created.
     
  • Enrolling: Data have been submitted to the NDA Collection or the NDA Data Expected initial submission date has been reached for at least one data structure category in the NDA Collection.
     
  • Data Analysis: Subject level data collection for the research project is completed and has been submitted to the NDA Collection.  The NDA Collection owner or the NDA Help Desk may set this phase when they’ve confirmed data submission is complete and submitted subject counts match at least 90% of the target enrollment numbers in the NDA Data Expected. Data submission reminders will be turned off for the NDA Collection.
     
  • Funding Completed: The NIH grant award (or awards) associated with the NDA Collection has reached its end date. NDA Collections in Funding Completed phase are assigned a subphase to indicate the status of data submission.
     
    • The Data Expected Subphase indicates that NDA expects more data will be submitted
    • The Closeout Subphase indicates the data submission is complete.
    • The Sharing Not Met Subphase indicates that data submission was not completed as expected. 

Blinded Clinical Trial Status:

  • This status is set by a Collection Owner and indicates the research project is a double blinded clinical trial.  When selected, the public view of Data Expected will show the Data Expected items and the Submission Dates, but the targeted enrollment and subjects submitted counts will not be displayed.
     
  • Targeted enrollment and subjects submitted counts are visible only to NDA Administrators and to the NDA Collection or as the NDA Collection Owner.
     
  • When an NDA Collection that is flagged Blinded Clinical Trial reaches the maximum data sharing date for that Data Repository (see https://nda.nih.gov/about/sharing-regimen.html), the embargo on Data Expected information is released.
     

Funding Source

The organization(s) responsible for providing the funding is listed here. 

Supporting Documentation

Users with Submission privileges, as well as Collection Owners, Program  Officers, and those with Administrator privileges, may upload and attach supporting documentation. By default, supporting documentation is shared to the general public, however, the option is also available to limit this information to qualified researchers only. 

Grant Information 

Identifiable details are displayed about the Project of which the Collection was derived from. You may click in the Project Number to view a full report of the Project captured by the NIH. 

Clinical Trials

Any data that is collected to support or further the research of clinical studies will be available here. Collection Owners and those with Administrator privileges may add new clinical trials. 

Frequently Asked Questions

  • When a Collection is created by NDA staff and marked as Shared, an email notification will automatically be sent to the PI(s) of the grant(s) associated with the Collection to notify them.

  • During Collection creation, NDA staff determine the appropriate Permission Group based on the type of data to be submitted, the type of access that will be available to data access users, and the information provided by the Program Officer during grant award.

  • The NDA system does not allow for a single grant to be associated with more than one Collection; therefore, a single grant will not be listed in the Grant Information section of a Collection for more than one Collection.

  • In general, each Collection is associated with only one grant; however, multiple grants may be associated if the grant has multiple competing segments for the same grant number or if multiple different grants are all working on the same project and it makes sense to hold the data in one Collection (e.g., Cooperative Agreements).

Glossary

  • Number of human subjects enrolled in an NIH-funded clinical research study. The data is provided in annual progress reports.

  • A privilege provided to a user associated with an NDA Collection or NDA Study whereby that user can perform a full range of actions including providing privileges to other users. 

  • Generally, the Collection Owner is the contact PI listed on a grant. Only one NDA user is listed as the Collection owner. Most automated emails are primarily sent to the Collection Owner.

  • The Collection Phase provides information on data submission as opposed to grant/project completion so while the Collection phase and grant/project phase may be closely related they are often different.  Collection users with Administrative Privileges are encouraged to edit the Collection Phase.  The Program Officer as listed in eRA (for NIH funded grants) may also edit this field. Changes must be saved by clicking the Save button at the bottom of the page.  This field is sortable alphabetically in ascending or descending order. Collection Phase options include: 

    • Pre-Enrollment:  A grant/project has started, but has not yet enrolled subjects.
    • Enrolling:  A grant/project has begun enrolling subjects.  Data submission is likely ongoing at this point.
    • Data Analysis:  A grant/project has completed enrolling subjects and has completed all data submissions.
    • Funding Completed:  A grant/project has reached the project end date.
  • The Collection State indicates whether the Collection is viewable and searchable.  Collections can be either Private, Shared, or an Ongoing Study.  A Collection that is shared does not necessarily have shared data as the Collection State and state of data are independent of each other.  This field can be edited by Collection users with Administrative Privileges and the Program Officer as listed in eRA (for NIH funded grants). Changes must be saved by clicking the Save button at the bottom of the page.

  • An editable field with the title of the Collection, which is often the title of the grant associated with the Collection.

  • Data Use Limitations (DULs) describe the appropriate secondary use of a dataset and are based on the original informed consent of a research participant. NDA only accepts consent-based data use limitations defined by the NIH Office of Science Policy.

  • Provides the grant number(s) for the grant(s) associated with the Collection.  The field is a hyperlink so clicking on the Grant number will direct the user to the grant information in the NIH Research Portfolio Online Reporting Tools (RePORT) page.

  • A virtual container and organization structure for data and associated documentation from one grant or one large project/consortium. It contains tools for tracking data submission and allows investigators to define a wide array of other elements that provide context for the data, including all general information regarding the data and source project, experimental parameters used to collect any event-based data contained in the Collection, methods, and other supporting documentation. They also allow investigators to link underlying data to an NDA Study, defining populations and subpopulations specific to research aims. 

  • NDA Collections may be organized by scientific similarity into NIH Research Initiatives, to facilitate query tool user experience. NIH Research Initiatives map to one or multiple Funding Opportunity Announcements. 

  • Access to shared record-level data in NDA is provisioned at the level of a Permission Group. NDA Permission Groups consist of one or multiple NDA Collections that contain data with the same subject consents.

  • Number of human subject participants to be enrolled in an NIH-funded clinical research study. The data is provided in competing applications and annual progress reports.

  • Various documents and materials to enable efficient use of the data by investigators unfamiliar with the project and may include the research protocol, questionnaires, and study manuals.  

  • The total number of unique subjects for whom data have been shared and are available for users with permission to access data.

NDA Help Center

Collection - Shared Data Tab

This tab provides a quick overview of the Data Structure title, Data Type, and Number of Subjects that are currently Shared for the Collection. The information presented in this tab is automatically generated by NDA and cannot be edited. If no information is visible on this tab, this would indicate the Collection does not have shared data or the data is private.

The shared data is available to other researchers who have permission to access data in the Collection's designated Permission Group(s). Use the Download button to get all shared data from the Collection to the Filter Cart.

 

Frequently Asked Questions

  • To see what data your project have submitted are being used by a study, simply go the Associated Studies tab of your collection.  Alternatively, you may review an NDA Study Attribution Report available on the General tab.  

  • Often it becomes more difficult to organize and format data electronically after the project has been completed and the information needed to create a GUID may not be available; however, you may still contact a program staff member at the appropriate funding institution for more information.

  • Unlike completed projects where researchers may not have the information needed to create a GUID and/or where the effort needed to organize and format data becomes prohibitive, ongoing projects have more of an opportunity to overcome these challenges.  Please contact a program staff member at the appropriate funding institution for more information.

Glossary

  • A defined organization and group of Data Elements to represent an electronic definition of a measure, assessment, questionnaire, or collection of data points.  Data structures that have been defined in the NDA Data Dictionary are available at https://ndar.nih.gov/data_dictionary.html. 

  • A grouping of data by similar characteristics such as Clinical Assessments, Omics, or Neurosignal data.

  • The term 'Shared' generally means available to others; however, there are some slightly different meanings based on what is Shared.  A Shared NDA Collection or NDA Study is viewable and searchable publicly regardless of the user's role or whether the user has an NDA account.  A Shared Collection or NDA Study does not necessarily mean that data submitted to the Collection or used in the NDA Study have been shared as this is independently determined.  Data are shared according the schedule defined in a Collection's Data Expected Tab and/or in accordance with data sharing expectations in the NDA Data Sharing Terms and Conditions.  Additionally, Supporting Documentation uploaded to a Collection may be shared independent of whether data are shared, but will only be viewable and accessible if the Collection is Shared.

NDA Help Center

fMRi

fMRI stands for functional magnetic resonance imaging. fMRI tests measure blood flow, providing detailed functional images of the brain or body. 

Acquisition
The Acquisition parameters needed for an experiment include the following:

The name of the experiment is required. Please be concise and specific as possible.
Following experiment name, selection boxes are provided for the Equipment, Software, or other items specific to the experiment type. At least one selection is required for each. If NDAR does not have the appropriate listing, select Add New to add the information provided. Following the selection boxes, provide additional information may be required depending on the experiment type. Any required items are denoted by an asterisk (*).

Block/Event Design
At least one block/event is required. Note that any fields denoted with an asterisk (*) are required. All data must be devoid of personally identifiable data, including the contents of any files attached to the experiment.

Note: To simplify the definition of multiple events, we provide an Import from XML function. This function supports importing data from all three experiment sections (Acquisition, Block/Event Design, and Post Processing), at this time files cannot be uploaded from XML A test format is provided here and our XML Schema Definition (xsd) can be found here.

Post Processing
If you have completed any post-processing on your data, please choose 'Yes' for Has Postprocessing? If not, select 'No'. Depending on this selection the remaining post-processing fields will be enabled (some of which will be required). If you are initially providing data you can select 'No', then return to the experiment to add post-processing steps at a later date when the data are being provided.

Please provide information about post-processing manipulations, i.e. artifact detection algorithms, segmentation used for post data collection, items denoted with an asterisk (*) are required.

Frequently Asked Questions

Glossary

  • This button will add all selections to the Filter Cart. 

  • This button will allow you to copy all of the Experiment details as a template for a new experiment. 

  • Adds all data from the current selections in a Collection or NDA Study to the Filter Cart.

  • This button will allow you to return to the Experiments tab. 

NDA Help Center

Collection - Submissions Tab

Users with permission to access Shared data in the Collection’s assigned Permission Group may use this tab. 

Here, you can:

  • Review your uploads to your Collection, monitor their status, and download them individually to verify their contents.
  • Download individual datasets as a secondary user of the data approved for access.
  • Identify and download datasets containing errors identified by NDA's QA/QC process for review and resolution.
  • Report suspected or discovered Personally Identifiable Information in a submission via the Actions column.

Frequently Asked Questions

Glossary

  • The default view of Datasets within a Collection's Submission tab.

  • A Submission Loading Status on a Collection's Submission Tab that indicates that an issue has prevented the successful loading of the submission.  Users should contact the NDA Help Desk for assistance at NDAHelp@mail.nih.gov.

  • The NDA has two Submission Cycles per year - January 15 and July 15.

  • An interface to notify NDA that data may not be submitted during the upcoming/current submission cycle.  

  • The unique and sequentially assigned ID for a submission (e.g. a discrete upload via the Validation and Upload Tool), which may contain any number of datafiles, Data Structures and/or Data Types, regardless of the Submission Loading Status. A single submission may be divided into multiple Datasets, which are based on Data Type.

  • The total number of unique subjects for whom data have been shared and are available for users with permission to access data.

  • The total number of unique subjects for whom data have been submitted, which includes data in both a Private State and a Shared State.

NDA Help Center

Collection - Publications Tab

The number of Publications is displayed in parentheses next to the tab name. Clicking on any of the Publication Titles will open the Publication in a new internet browsing tab. 

Collection Owners, Program Officers, and users with Submission or Administrative Privileges for the Collection may mark a publication as either Relevant or Not Relevant in the Status column. 

 

Frequently Asked Questions

  • Publications are considered relevant to a collection when the data shared is directly related to the project or collection.

  • PubMed, an online library containing journals, articles, and medical research. Sponsored by NiH and National Library of Medicine (NLM). 

Glossary

  • A link to the Create an NDA Study page that can be clicked to start creating an NDA Study with information such as the title, journal and authors automatically populated.

  • Indicates that the publication has not yet been reviewed and/or marked as Relevant or Not Relevant so it has not been determined whether an NDA Study is expected.

  • A publication that is not based on data related to the aims of the grant/project associated with the Collection or not based on any data such as a review article and, therefore, an NDA Study is not expected to be created.

  • PubMed provides citation information for biomedical and life sciences publications and is managed by the U.S. National Institutes of Health's National Library of Medicine.

  • The PUBMed ID is the unique ID number for the publication as recorded in the PubMed database.  

  • A publication that is based on data related to the aims of the grant/project associated with the Collection and, therefore, an NDA Study is expected to be created.

NDA Help Center

EEG

EEG stands for electroencencephalogram and is a test used to measure electrical activity in the brain.

Acquisition
The Acquisition parameters needed for an experiment include the following:

Name of the experiment is required. Please be concise and specific as possible.
Following experiment name, selection boxes are provided for the Equipment, Software, or other items specific to experiment type. At least one selection is required for each. If NDAR does not have the appropriate listing, select Add New to add the information provided. Following the selection boxes, provide additional information may be required depending on experiment type. Any required items are denoted by an asterisk (*).

Block/Event Design
At least one block/event is required. Note that any fields denoted with an asterisk (*) are required. All data must be devoid of personally identifiable data, including the contents of any files attached to the experiment.

Note: To simplify definition of multiple events, we provide an Import from XML function. This function supports importing data from all three experiment sections (Acquisition, Block/Event Design, and Post Processing), at this time files cannot be uploaded from XML A test format is provided here and our XML Schema Definition (xsd) can be found here.

Post Processing
If you have completed any post processing on your data, please choose 'Yes' for Has Postprocessing? If not, select 'No'. Depending on this selection the remaining post processing fields will be enabled (some of which will be required). If you are initially providing data you can select 'No', then return to the experiment to add post processing steps at a later date when the data are being provided.

Please provide information about post-processing manipulations, i.e. artifact detection algorithms, segmentation used for post data collection, items denoted with an asterisk (*) are required.

Frequently Asked Questions

Glossary

  • This button will add all selections to the Filter Cart. 

  • This button will allow you to copy all of the Experiment details as a template for a new experiment. 

  • Adds all data from the current selections in a Collection or NDA Study to the Filter Cart.

  • This button will allow you to return to the Experiments tab. 

NDA Help Center

Collection - Data Expected

The Data Expected tab displays the list of all data that NDA expects to receive in association with the Collection as defined by the contributing researcher, as well as the dates for the expected initial upload of the data, and when it is first expected to be shared, or with the research community. Above the primary table of Data Expected, any publications determined to be relevant to the data within the Collection are also displayed - members of the contributing research group can use these to define NDA Studies, connecting those papers to underlying data in NDA.

The tab is used both as a reference for those accessing shared data, providing information on what is expected and when it will be shared, and as the primary tracking mechanism for contributing projects. It is used by both contributing primary researchers, secondary researchers, and NIH Program and Grants Management staff.

Contributing researchers just getting started on their project will need to define this list by adding all of the items they are collecting under their grant and setting their schedule according to the NDA Data Sharing Regimen. If you fall into this category, you can begin by clicking "add new Data Expected" and selecting which data structures you will be using, saving the page after each change, or requesting new structures by adding and naming a new item, providing any materials NDA Data Dictionary Curators can use to help define your structure. For more information see the tutorial on creating Data Expected.

If you are a contributing researcher creating this list for the first time, or making changes to the list as your project progress, please note the following:

  • Although items you add to the list and changes you make are displayed, they are not committed to the system until you Save the entire page using the "Save" button at the bottom of your screen. Please Save after every change to ensure none of your work is lost.
  • If you attempt to add a new structure, the title you provide must be unique - if another structure exists with the same name your change will fail.
  • Adding a new structure to this list is the only way to request the creation of a new Data Dictionary definition.

 

Frequently Asked Questions

  • An NDA Data Structure is comprised of multiple Data Elements to make up an electronic definition of an assessment, measure, questionnaire, etc will have a corresponding Data Structure.

  • The NDA Data Dictionary is comprised of electronic definitions known as Data Structures.

Glossary

  • Data specific to the primary aims of the research being conducted (e.g. outcome measures, other dependent variables, observations, laboratory results, analyzed images, volumetric data, etc.) including processed images.

  • Items listed on the Data Expected list in the Collection which may be an individual and discrete Data Structure, Data Structure Category, or Data Structure Group.

  • A defined organization and group of Data Elements to represent an electronic definition of a measure, assessment, questionnaire, or collection of data points.  Data structures that have been defined in the NDA Data Dictionary are available at https://ndar.nih.gov/data_dictionary.html. 

  • An NDA term describing the affiliation of a Data Structure to a Category, which may be disease/disorder or diagnosis related (Depression, ADHD, Psychosis), specific to data type (MRI, eye tracking, omics), or type of data (physical exam, IQ).

  • A Data Item listed on the Data Expected tab of a Collection that indicates a group of Data Structures (e.g., ADOS or SCID) for which data may be submitted instead of a specific Data Structure identified by version, module, edition, etc. For example, the ADOS Data Structure Category includes every ADOS Data Structure such as ADOS Module 1, ADOS Module 2, ADOS Module 1 - 2nd Edition, etc. The SCID Data Structure Group includes every SCID Data Structure such as SCID Mania, SCID V Mania, SCID PTSD, SCID-V Diagnosis, and more. 

  • A new Data Structure category, Evaluated Data is analyzed data resulting from the use of computational pipelines in the Cloud and can be uploaded directly back to a miNDAR database.  Evaluated Data is expected to be listed as a Data Item in the Collection's Data Expected Tab.

  • Imaging+ is an NDA term which encompasses all imaging related data including, but not limited to, images (DTI, MRI, PET, Structural, Spectroscopy, etc.) as well as neurosignal data (EEG, fMRI, MEG, EGG, eye tracking, etc.) and Evaluated Data.

  • Initial Submission and Initial Share dates should be populated according to the NDA Data Sharing Terms and Conditions. Any modifications to these will go through the approval processes outlined above. Data will be shared with authorized users upon publication (via an NDA Study) or 1-2 years after the grant end date specified on the first Notice of Award, as defined in the applicable Data Sharing Terms and Conditions.

  • Initial Submission and Initial Share dates should be populated according to these NDA Data Sharing Terms and Conditions. Any modifications to these will go through the approval processes outlined above. Data for all subjects is not expected on the Initial Submission Date and modifications may be made as necessary based on the project's conduct.

  • An NDA created Data Structure used to convey basic information about the subject such as demographics, pedigree (links family GUIDs), diagnosis/phenotype, and sample location that are critical to allow for easier querying of shared data.

  • The NDA has two Submission Cycles per year - January 15 and July 15.

  • An interface to notify NDA that data may not be submitted during the upcoming/current submission cycle.  

NDA Help Center

Collection - Permissions Tab

Collection Owners, Program Officers, and users with Administrator privileges may view this tab.

The available permission groups include:

  • Query: This read-only access is generally for NIH Program Officers
  • Submission: This will grant read access and allow the user to upload data and create experiment definitions. This is for the typical contributing personnel member.
  • Administrator: In addition to the access provided to Query and Submission users, Admins can also edit the Collection itself, create or edit the Data Expected list, and edit user permissions. This access is for the PI, data managers, and anyone they wish to delegate this to.

The PI has a special designation as the Collection Owner in addition to administrator access.

Frequently Asked Questions

  • Collection Owners and Admins may assign Collection Privileges to anyone.

  • Yes, you can assign various Privileges to other users with an NDA account.

  • If you are the Collection Owner or have Admin privileges, you can view and make changes to the list of individuals who have access to the Collection on the Collection's Permissions tab.  Information on users who have access to data Shared in your Collection because they were granted access to a Permission Group is not available.

  • Staff/collaborators who are working submitting data to the Collection, checking the quality of the data, and/or analyzing data should have access for the duration of the project until all data have been submitted, NDA Studies have been created for data used in publications, and/or a collaborative relationship with the user exists.  

  • The individual listed as an Investigator on the General tab of the NDA Collection will generally be able to provide a user access to the NDA Collection.  Additional users may also have this ability if granted Administrator access to an NDA Collection; however, these users are not viewable unless your account has access to the NDA Collection.  Given this, it is best to contact the Investigator to request access to the Collection.

  • Privileges that can be assigned to a user include:
    Submission allows a user to submit data to Collection
    Query allows the user to download data from Collection even when in a Private state
    Admin is both the Submission and Query Privilege + the ability to give privileges to other users.

  • You may have staff who are working on the submission of data or other activities associated with data sharing such as the definition of the Data Expected list or NDA Experiment creation.  Also, many projects have multiple performance sites and wish to share data among the site PIs.  Submitting to the NDA facilitates access by all investigators working on a project even before data have been shared with other users.  You can control who gets access to data while in a Private state.

Glossary

  • A privilege provided to a user associated with an NDA Collection or NDA Study whereby that user can perform a full range of actions including providing privileges to other users. 

  • Access to shared record-level data in NDA is provisioned at the level of a Permission Group. NDA Permission Groups consist of one or multiple NDA Collections that contain data with the same subject consents.

NDA Help Center

Eye Tracking

EyeTracking tests follow the movement of the eye. The visual trajectory or focus can help determine predictions and assist in diagnoses. 

Acquisition
The Acquisition parameters needed for an experiment include the following:

The name of the experiment is required. Please be concise and specific as possible.
Following experiment name, selection boxes are provided for the Equipment, Software, or other items specific to the experiment type. At least one selection is required for each. If NDAR does not have the appropriate listing, select Add New to add the information provided. Following the selection boxes, provide additional information may be required depending on the experiment type. Any required items are denoted by an asterisk (*).

Block/Event Design
At least one block/event is required. Note that any fields denoted with an asterisk (*) are required. All data must be devoid of personally identifiable data, including the contents of any files attached to the experiment.

Note: To simplify the definition of multiple events, we provide an Import from XML function. This function supports importing data from all three experiment sections (Acquisition, Block/Event Design, and Post Processing), at this time files cannot be uploaded from XML A test format is provided here and our XML Schema Definition (xsd) can be found here.

Post Processing
If you have completed any post-processing on your data, please choose 'Yes' for Has Postprocessing? If not, select 'No'. Depending on this selection the remaining post-processing fields will be enabled (some of which will be required). If you are initially providing data you can select 'No', then return to the experiment to add post-processing steps at a later date when the data are being provided.

Please provide information about post-processing manipulations, i.e. artifact detection algorithms, segmentation used for post data collection, items denoted with an asterisk (*) are required.

Frequently Asked Questions

Glossary

  • This button will add all selections to the Filter Cart. 

  • This button will allow you to copy all of the Experiment details as a template for a new experiment. 

  • Adds all data from the current selections in a Collection or NDA Study to the Filter Cart.

  • This button will allow you to return to the Experiments tab. 

NDA Help Center

Collection - Experiments Tab

The number of Experiments included is displayed in parentheses next to the tab name. You may download all experiments associated with the Collection via the Download button. You may view individual experiments by clicking the Experiment Name and add them to the Filter Cart via the Add to Cart button.

Collection Owners, Program Officers, and users with Submission or Administrative Privileges for the Collection may create or edit an Experiment.

Please note: The creation of an NDA Experiment does not necessarily mean that data collected, according to the defined Experiment, has been submitted or shared.

Frequently Asked Questions

  • Yes -see the “Copy” button in the bottom left when viewing an experiment. There are two actions that can be performed via this button:

    1. Copy the experiment with intent for modifications.  
    2. Associate the experiment to the collection. No modifications can be made to the experiment.

     

Glossary

  • An Experiment must be Approved before data using the associated Experiment_ID may be uploaded.

  • The ID number automatically generated by NDA which must be included in the appropriate file when uploading data to link the Experiment Definition to the subject record.

NDA Help Center

Omics

Omics is a collective group of technologies, related to a field of study in Biology such as Genomics or proteomics. 

Experiment Parameters

To define an Omics experiment, provide a meaningful name and select a single molecule. The standard molecules are listed. However, if you are doing proteomic or environmental experiments, simply “Add New” and the new selection will be created. Only one value for molecule is permitted.

Next the technology (box 2) associated with the molecule will be presented along with its application. Again, only one selection is possible. If you wish to see all of NDAR’s options for any one box, Select “Show All”.

Platform

Continue to select the Platform (box 3).

Extraction

Next, the Extraction Protocol (box 4) and Kits (box 5) are presented based upon the Molecule selected and the Processing Protocol (box 6) and Kits (box 7) are presented based upon the Molecule and Technology Application (Box 1 and 2)

Processing

Note that for each of these (boxes 4, 5, 6, and 7) multiple selections are possible.

Additional Information

Lastly, the Software (box 8) and Equipment (box 9) is expected.

 

Once saved, the experiment will be associated with the Collection and by using the returned Experiment_ID, the NDA makes it possible to associate the experiment meta data directly with the data from the experiment.

Frequently Asked Questions

Glossary

  • This button will add all selections to the Filter Cart. 

  • This button will allow you to copy all of the Experiment details as a template for a new experiment. 

  • Adds all data from the current selections in a Collection or NDA Study to the Filter Cart.

  • This button will allow you to return to the Experiments tab. 

NDA Help Center

Filter Cart

Viewable at the top right of NDA pages, the Filter Cart is a temporary holder for filters and data they select. Filters are added to the Workspace first, before being submitted to The Filter Cart. Data selected by filters in the Filter Cart can be added to a Data Package or an NDA Study from the Data Packaging Page, by clicking the 'Create Data Package / Add Data to Study' button.

The filter cart supports combining multiple filters together, and depending on filter type will use "AND" or "OR"  when combining filters.

Multiple selections from the same filter type will result in those selections being applied with an ‘OR’ condition. For example, if you add an NDA Collection Filter with selections for both collections 2112 and 2563 to an empty Workspace, the subjects from NDA Collection 2112 ‘OR’ NDA Collection 2563 will be added to your Workspace even if a subject is in both NDA Collections. You can then add other NDA Collections to your Workspace which further extends the ‘OR’ condition.

If a different filter type is added to your Workspace, or a filter has already been submitted to the Filter Cart, the operation then performs a logical ‘AND’ operation. This means that given the subjects returned from the first filter, only those subjects that matched the first filter are returned by the second filter (i.e., subjects that satisfied both filters).

When combining other filters with the GUID filter, please note the GUID filter should be added last. Otherwise, preselected data may be lost. For example, a predefined filter from Featured Datasets may select a subset of data available for a subject. When combined with a GUID filter for the same subject, the filter cart will contain all data available from that subject, data structure, and dataset; this may be more data than was selected in the predefined filter for that subject. Again, you should add the GUID Filter as the last filter to your cart. This ensures 'AND' logic between filters and will limit results to the subjects, data structures, and datasets already included in your filter cart.

Note that only the subjects specific to your filter will be added to your Filter Cart and only on data shared with the research community. Other data for those same subjects may exist (i.e., within another NDA Collection, associated with a data structure that was not requested in the query, etc.). So, users should select ‘Find all Subjects Data’ to identify all data for those specific subjects. 

Additional Tips:

  • You may query the data without an account, but to gain access you will need to create an NDA user account and apply for access.  Most data access requires that you or your lab are sponsored by an NIH recognized institution with Federal Wide Assurance (FWA).  Without access, you will not be able to obtain individual-level data. 

    Once you have selected data of interest you can:
  • Create a data package - This allows you to specify format for access/download
  • Assign to Study Cohort - Associate the data to an NDA Study allowing for a DOI to be generated and the data to be linked directly to a finding, publication, or data release. 
  • Find All Subject Data - Depending on filter types being used, not all data associated with a subject will be selected.  Data may be restricted by data structure, NDA Collection, or outcome variables (e.g., NDA Study). ‘Find All Data’ expands the fliter criteria by replacing all filters in your Filter Cart with a single Query by GUID filter for all subjects selected by those filters.

    Please Note:
  • When running a query, it may take a moment to populate the Filter Cart. Queries happen in the background so you can define other queries during this time. 
  • When you add your first filter, all data associated with your query will be added to the Filter Cart (e.g., a Concept, an NDA Collection, a Data Structure/Element, etc.). As you add additional filters, they will also display in the Filter Cart. Only the name of filter will be shown in the Filter Cart, not the underlying structures. 
  • Information about the contents of the Filter Cart can be seen by clicking "Edit”.
  • Once your results appear in the Filter Cart, you can create a data package or assign subjects to a study by selecting the 'Package/Assign to Study' option. You can also 'Edit' or 'Clear' filters.
     

Frequently Asked Questions

  • The Filter Cart currently employs basic AND/OR Boolean logic. A single filter may contain multiple selections for that filter type, e.g., a single NDA Study filter might contain NDA Study 1 and NDA Study 2. A subject that is in EITHER 1 OR 2 will be returned.  Adding multiple filters to the cart, regardless of type, will AND the result of each filter.  If NDA Study 1 and NDA Study 2 are added as individual filters, data for a subject will only be selected if the subject is included in  BOTH 1 AND 2.

    When combining other filters with the GUID filter, please note the GUID filter should be added last. Otherwise, preselected data may be lost. For example, a predefined filter from Featured Datasets may select a subset of data available for a subject. When combined with a GUID filter for the same subject, the filter cart will contain all data available from that subject, data structure, and dataset; this may be more data than was selected in the predefined filter for that subject. Again, you should add the GUID Filter as the last filter to your cart. This ensures 'AND' logic between filters and will limit results to the subjects, data structures, and datasets already included in your filter cart.

  • Viewable at the top right of NDA pages, the Filter Cart is a temporary holder of data identified by the user, through querying or browsing, as being of some potential interest. The Filter Cart is where you send the data from your Workspace after it has been filtered.

  • After filters are added to the Filter Cart, users have options to ‘Create a Package’ for download, ‘Associate to Study Cohort’, or ‘Find All Subject Data’. Selecting ‘Find All Subject Data’ identifies and pulls all data for the subjects into the Filter Cart. Choosing ‘Create a Package’ allows users to package and name their query information for download. Choosing ‘Associate to Study Cohort’ gives users the opportunity to choose the Study Cohort they wish to associate this data.

Glossary

  • Once your filter cart contains the subjects of interest, select Create Data Package/Assign to Data Study which will provide options for accessing item level data and/or assigning to a study.  

  • Once queries have been added to your workspace, the next step is to Submit the Filters in the workspace to the Filter Cart.  This process runs the queries selected, saving the results within a filter cart attached to your account.  

  • The Workspace within the General Query Tool is a holding area where you can review your pending filters prior to adding them to Filter Cart. Therefore, the first step in accessing data is to select one or more items and move it into the Workspace. 

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Collection - Associated Studies

Clicking on the Study Title will open the study details in a new internet browser tab. The Abstract is available for viewing, providing the background explanation of the study, as provided by the Collection Owner. 

Primary v. Secondary Analysis: The Data Usage column will have one of these two choices. An associated study that is listed as being used for Primary Analysis indicates at least some and potentially all of the data used was originally collected by the creator of the NDA Study. Secondary Analysis indicates the Study owner was not involved in the collection of data, and may be used as supporting data. 

Private v. Shared State: Studies that remain private indicate the associated study is only available to users who are able to access the collection. A shared study is accessible to the general public. 

Frequently Asked Questions

  • Studies are associated to the Collection automatically when the data is defined in the Study. 

Glossary

  • A tab in a Collection that lists the NDA Studies that have been created using data from that Collection including both Primary and Secondary Analysis NDA Studies.

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1 Numbers reported are subjects by age
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Format should be in the following format: Activity Code, Institute Abbreviation, and Serial Number. Grant Type, Support Year, and Suffix should be excluded. For example, grant 1R01MH123456-01A1 should be entered R01MH123456

Please select an experiment type below

Collection - Use Existing Experiment

To associate an experiment to the current collection, just select an axperiment from the table below then click the associate experiment button to persist your changes (saving the collection is not required). Note that once an experiment has been associated to two or more collections, the experiment will not longer be editable.

The table search feature is case insensitive and targets the experiment id, experiment name and experiment type columns. The experiment id is searched only when the search term entered is a number, and filtered using a startsWith comparison. When the search term is not numeric the experiment name is used to filter the results.

SelectExperiment IdExperiment NameExperiment Type
  • Select One
  • EEG
  • EGG
  • Eye Tracking
  • Omics
  • fMRI
Created On
1869RRAY fMRI ScanfMRI11/27/2021
1867Resting StatefMRI11/22/2021
1866MNA fMRIfMRI11/16/2021
1865Motion AftereffectsEye Tracking11/05/2021
1864Tilt Aftereffects (TAE)Eye Tracking11/05/2021
1863Negative Afterimages (AI)Eye Tracking11/05/2021
1862Face-Matching TaskfMRI11/03/2021
1861Resting StatefMRI11/03/2021
1860CARIT (Go/NoGo Task)fMRI11/03/2021
1859PCR-free sequencingOmics10/29/2021
1858GNG Anger, Gender, Happy Tasks- EEGEEG10/15/2021
1857PVDM, imaging sessionEye Tracking10/14/2021
1856PVDM, imaging sessionfMRI10/13/2021
1855PVDM, behavioral sessionEye Tracking10/13/2021
1854Cerebellar Dysfunction in Autism: resting state fMRIfMRI10/13/2021
1852snRNAseq_controls_DLPFC/sgACCOmics09/30/2021
1851Reappraisal Emotion Regulation Task - V2fMRI09/22/2021
1850Reappraisal Emotion Regulation Task - V1fMRI09/22/2021
1849Stop-Signal Arrows - Randomization BfMRI09/22/2021
1848Stop-Signal Arrows - Randomization AfMRI09/22/2021
1847NPU Threat Countdown Short - V2fMRI09/22/2021
1846NPU Threat Countdown Short - V1fMRI09/22/2021
1836Alcohol Cue ReactivityEEG09/02/2021
1835Doors Reward ParadigmEEG08/30/2021
1834Flanker ArrowsEEG08/30/2021
1833Transcriptomic data of Clozapine-treated Ngn2-induced Human Excitatory NeuronsOmics08/20/2021
1830Illumina Global Screening ArrayOmics08/02/2021
1829Single-cell multiome sequencing: ATAC-seqOmics07/26/2021
1828Single-cell multiome sequencing - RNA-seqOmics07/26/2021
1827scATACseqOmics07/26/2021
1826scRNAseqOmics07/26/2021
1825Fetal Resting-state fMRI Brain MasksfMRI07/23/2021
1824Apex of Cognitive ControlfMRI07/22/2021
1823Face adaptationEye Tracking07/21/2021
1822Presaccadic AttentionEye Tracking07/21/2021
1821templefMRI07/19/2021
1820parvizi_eeg_145EEG07/16/2021
1819parvizi_eeg_166EEG07/16/2021
1818parvizi_eeg_164EEG07/16/2021
1817parvizi_eeg_165EEG07/16/2021
1816parvizi_eeg_162EEG07/16/2021
1815parvizi_eeg_161EEG07/16/2021
1814eeg_parvizi_160EEG07/16/2021
1813parvizi_eeg_159EEG07/16/2021
1812Singleton distractor rejectionEEG07/16/2021
1810InterlayerfMRI07/15/2021
1809Alpha, BOLD, experience, and expectancy during associative learningEEG07/14/2021
1808Alpha, BOLD, experience, and expectancy during associative learningfMRI07/14/2021
1807Correlating concurrent EEG/BOLD in occipital cortex while presenting Gabor patch steadily increasing in contrastEEG07/14/2021
1806Correlating concurrent EEG/BOLD in occipital cortex while presenting Gabor patch steadily increasing in contrastfMRI07/14/2021
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Collection Summary Collection Charts
Collection Title Collection Investigators Collection Description
1/3, 2/3, and 3/3: Sequencing Autism Spectrum Disorder Extended Pedigrees
Gerard Schellenberg, Hilary Coon and Ellen Wijsman 
We have in hand a unique resource of extended autism spectrum disorder (ASD) pedigrees. We will sequence family members from the most informative pedigrees to study genetic variation contributing to ASD and related phenotypes. We will work to discover new variation, and also use the resource to characterize variants in conjunction with existing whole exome data available through our collaborations. We will test findings in up to 10 other families available from the Autism Genome Project (AGP) network of collaborators. We will also make the resource available to the broader scientific community. Extended families offer an excellent opportunity to identify and study genetic variation, giving a complementary approach to ongoing studies of simplex and small multiplex families. The current collection of families represents some of the largest pedigrees with ASD in the world. We have already detected significant linkage evidence in some of these families with clinical diagnosis and also with related phenotypes. Sequence data in these extended families will result in highly accurate and complete genetic information. We will identify familial variation in these data, and predict potentially damaging variants using new informatics approaches. We will refine information about risk by comparing to ongoing sequence projects. We will also use the ongoing sequence projects to help prioritize the familial variant discovery, and choose the best for replication efforts in other AGP families. Finally, we will investigate sequence variants found by simplex/small family sequencing to determine specificity and penetrance in our extended families. Our proposed project will benefit from the continued collaboration of world-class molecular, analytic, and clinical expertise in the Autism Genome Project to enable the most effective use of this unique resource.
NIMH Data Archive
NIMH Data Archive
Funding Completed
Close Out
Shared
No
$3,422,258.00
3,715
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NIH - Extramural None

Summary_Information_for_SNP_Linkage_Analysis_Data.pdf Background Summary Information for SNP Linkage Analysis Data Qualified Researchers

R01MH094293-01 2/3 Sequencing Autism Spectrum Disorder Extended Pedigrees 06/01/2012 04/30/2018 55 Not Reported UNIVERSITY OF WASHINGTON $1,149,418.00
R01MH094400-01 1/3 - Sequencing Autism Spectrum Disorder Extended Pedigrees 06/01/2012 02/28/2018 4 102 UNIVERSITY OF UTAH $1,479,240.00
R01MH094382-01 3/3-Sequencing Autism Spectrum Disorder Extended Pedigrees 06/01/2012 04/30/2017 Not Reported Not Reported UNIVERSITY OF PENNSYLVANIA $793,600.00

IDNameCreated DateStatusType
110Genotyping Project11/14/2013ApprovedOmics
136OmniExpressMarch201403/11/2014ApprovedOmics
137pedigree exomes March 201403/13/2014ApprovedOmics
392SNP genome scan-410/29/2015ApprovedOmics
393SNP genome scan-510/29/2015ApprovedOmics
394SNP genome scan-610/29/2015ApprovedOmics
395SNP genome scan-710/29/2015ApprovedOmics
396SNP genome scan-810/29/2015ApprovedOmics
397SNP genome scan-910/29/2015ApprovedOmics

Collection Owners and those with Collection Administrator permission, may edit a collection. The following is currently available for Edit on this page:

Shared Data

Data structures with the number of subjects submitted and shared are provided.

Aberrant Behavior Checklist (ABC) - Community Clinical Assessments 693
Anthropometric Information Clinical Assessments 1962
Autism Diagnostic Interview - Cumulative Clinical Assessments 430
Autism Diagnostic Observation Schedule (ADOS) - Module 4 Clinical Assessments 326
Autism Diagnostic Observation Schedule (ADOS)- Module 1 Clinical Assessments 172
Autism Diagnostic Observation Schedule (ADOS)- Module 2 Clinical Assessments 161
Autism Diagnostic Observation Schedule (ADOS)- Module 3 Clinical Assessments 267
BASC Parent Rating Scale Adolescent Clinical Assessments 466
Broad Autism Phenotype Questionnaire (BAPQ) Clinical Assessments 482
CADS-P Clinical Assessments 443
CELF Preschool Clinical Assessments 138
CELF-3 Clinical Eval of Lang Fundamentals, 3th ed Clinical Assessments 362
CELF-4 Clinical Eval of Lang Fundamentals, 4th ed Clinical Assessments 94
Comprehensive Test of Phonological Processing (CTOPP) Clinical Assessments 1090
DAS-II: Differential Ability Scales 2nd Ed. School Age Clinical Assessments 175
Developmental Behavior Checklist Clinical Assessments 195
Expanded Token Test Clinical Assessments 696
Genomics Sample Genomics 803
Genomics Subject Genomics 1689
Leiter International Performance Scale-Revised (Leiter-R), Visualization and Reasoning Battery Clinical Assessments 8
Mullen Scales of Early Learning Clinical Assessments 42
Peabody Picture Vocabulary Test, Fourth Edition-Form A Clinical Assessments 526
Repetitive Behavior Scales - Early Childhood Supplement Clinical Assessments 224
SRS-2. Adult, Preschool and School Age Clinical Assessments 1601
Social Communication Questionnaire (SCQ) - Lifetime Clinical Assessments 581
Stanford-Binet Intelligence Scales, Fifth Edition (SB5) Clinical Assessments 43
Vineland I Clinical Assessments 390
Vineland-II - Parent and Caregiver Rating Form (2005) Clinical Assessments 318
Wechsler Abbreviated Scale of Intelligence (WASI) Clinical Assessments 660
Wechsler Adult Intelligence Scale Fourth Edition [part 1] Clinical Assessments 109
Wechsler Adult Intelligence Scale III Clinical Assessments 338
Wechsler Intelligence Scale for Children III Clinical Assessments 166

Collection Owners and those with Collection Administrator permission, may edit a collection. The following is currently available for Edit on this page:

Publications

Publications relevant to NDA data are listed below. Most displayed publications have been associated with the grant within Pubmed. Use the "+ New Publication" button to add new publications. Publications relevant/not relevant to data expected are categorized. Relevant publications are then linked to the underlying data by selecting the Create Study link. Study provides the ability to define cohorts, assign subjects, define outcome measures and lists the study type, data analysis and results. Analyzed data and results are expected in this way.

PubMed IDStudyTitleJournalAuthorsDateStatus
31410696Create StudyEarly Second Trimester Maternal Serum Steroid-Related Biomarkers Associated with Autism Spectrum Disorder.Journal of autism and developmental disordersBilder, Deborah A; Esplin, M Sean; Coon, Hilary; Burghardt, Paul; Clark, Erin A S; Fraser, Alison; Smith, Ken R; Worsham, Whitney; Chappelle, Katlin; Rayner, Thomas; Bakian, Amanda VNovember 2019Not Determined
30545852Create StudyGenome-wide de novo risk score implicates promoter variation in autism spectrum disorder.Science (New York, N.Y.)An, Joon-Yong; Lin, Kevin; Zhu, Lingxue; Werling, Donna M; Dong, Shan; Brand, Harrison; Wang, Harold Z; Zhao, Xuefang; Schwartz, Grace B; Collins, Ryan L; Currall, Benjamin B; Dastmalchi, Claudia; Dea, Jeanselle; Duhn, Clif; Gilson, Michael C; Klei, Lambertus; Liang, Lindsay; Markenscoff-Papadimitriou, Eirene; Pochareddy, Sirisha; Ahituv, Nadav; Buxbaum, Joseph D; Coon, Hilary; Daly, Mark J; Kim, Young Shin; Marth, Gabor T; Neale, Benjamin M; Quinlan, Aaron R; Rubenstein, John L; Sestan, Nenad; State, Matthew W; Willsey, A Jeremy; Talkowski, Michael E; Devlin, Bernie; Roeder, Kathryn; Sanders, Stephan JDecember 2018Not Determined
30276537Create StudyReplication of a rare risk haplotype on 1p36.33 for autism spectrum disorder.Human geneticsChapman, N H; Bernier, R A; Webb, S J; Munson, J; Blue, E M; Chen, D-H; Heigham, E; Raskind, W H; Wijsman, Ellen MOctober 2018Not Determined
30246047Create StudyAutism Spectrum Disorder and Neonatal Serum Magnesium Levels in Preterm Infants.Child neurology openBakian, Amanda V; Bilder, Deborah A; Korgenski, E Kent; Bonkowsky, Joshua LJanuary 2018Not Determined
29523860Create StudyAllele-specific expression in a family quartet with autism reveals mono-to-biallelic switch and novel transcriptional processes of autism susceptibility genes.Scientific reportsLin, Chun-Yen; Chang, Kai-Wei; Lin, Chia-Yi; Wu, Jia-Ying; Coon, Hilary; Huang, Pei-Hsin; Ho, Hong-Nerng; Akbarian, Schahram; Gau, Susan Shur-Fen; Huang, Hsien-SungMarch 2018Not Determined
29389935Create StudyNovel pedigree analysis implicates DNA repair and chromatin remodeling in multiple myeloma risk.PLoS geneticsWaller, Rosalie G; Darlington, Todd M; Wei, Xiaomu; Madsen, Michael J; Thomas, Alun; Curtin, Karen; Coon, Hilary; Rajamanickam, Venkatesh; Musinsky, Justin; Jayabalan, David; Atanackovic, Djordje; Rajkumar, S Vincent; Kumar, Shaji; Slager, Susan; Middha, Mridu; Galia, Perrine; Demangel, Delphine; Salama, Mohamed; Joseph, Vijai; McKay, James; Offit, Kenneth; Klein, Robert J; Lipkin, Steven M; Dumontet, Charles; Vachon, Celine M; Camp, Nicola JFebruary 1, 2018Not Determined
29267877Create StudyGIGI-Quick: a fast approach to impute missing genotypes in genome-wide association family data.Bioinformatics (Oxford, England)Kunji, Khalid; Ullah, Ehsan; Nato Jr, Alejandro Q; Wijsman, Ellen M; Saad, MohamadMay 2018Not Determined
29266823Create StudyMid-life social outcomes for a population-based sample of adults with ASD.Autism research : official journal of the International Society for Autism ResearchFarley M, Cottle KJ, Bilder D, Viskochil J, Coon H, Mcmahon WJanuary 2018Not Determined
28968627Create StudyAssociation score testing for rare variants and binary traits in family data with shared controls.Briefings in bioinformaticsSaad, Mohamad; Wijsman, Ellen MJanuary 2019Not Determined
28540026Create StudyMeta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia.Molecular autismAutism Spectrum Disorders Working Group of The Psychiatric Genomics ConsortiumJanuary 1, 2017Not Determined
28504703Create StudyPolygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders.Nature geneticsWeiner, Daniel J; Wigdor, Emilie M; Ripke, Stephan; Walters, Raymond K; Kosmicki, Jack A; Grove, Jakob; Samocha, Kaitlin E; Goldstein, Jacqueline I; Okbay, Aysu; Bybjerg-Grauholm, Jonas; Werge, Thomas; Hougaard, David M; Taylor, Jacob; iPSYCH-Broad Autism Group; Psychiatric Genomics Consortium Autism Group; Skuse, David; Devlin, Bernie; Anney, Richard; Sanders, Stephan J; Bishop, Somer; Mortensen, Preben Bo; Børglum, Anders D; Smith, George Davey; Daly, Mark J; Robinson, Elise BJuly 2017Not Determined
28289475Create StudyCombined genome-wide linkage and targeted association analysis of head circumference in autism spectrum disorder families.Journal of neurodevelopmental disordersWoodbury-Smith M, Bilder DA, Morgan J, Jerominski L, Darlington T, Dyer T, Paterson AD, Coon HJanuary 2017Not Determined
27980662Create StudyEstimating relationships between phenotypes and subjects drawn from admixed families.BMC proceedingsBlue, Elizabeth M; Brown, Lisa A; Conomos, Matthew P; Kirk, Jennifer L; Nato Jr, Alejandro Q; Popejoy, Alice B; Raffa, Jesse; Ranola, John; Wijsman, Ellen M; Thornton, TimothyJanuary 2016Not Relevant
27980652Create StudyIdentity-by-descent estimation with population- and pedigree-based imputation in admixed family data.BMC proceedingsSaad, Mohamad; Nato Jr, Alejandro Q; Grimson, Fiona L; Lewis, Steven M; Brown, Lisa A; Blue, Elizabeth M; Thornton, Timothy A; Thompson, Elizabeth A; Wijsman, Ellen MJanuary 2016Not Relevant
27956748Create StudyAssociation of rare missense variants in the second intracellular loop of NaV1.7 sodium channels with familial autism.Molecular psychiatryRubinstein, M; Patowary, A; Stanaway, I B; McCord, E; Nesbitt, R R; Archer, M; Scheuer, T; Nickerson, D; Raskind, W H; Wijsman, E M; Bernier, R; Catterall, W A; Brkanac, ZFebruary 1, 2018Relevant
27562213Create StudyVARPRISM: incorporating variant prioritization in tests of de novo mutation association.Genome medicineHu, Hao; Coon, Hilary; Li, Man; Yandell, Mark; Huff, Chad DAugust 2016Not Determined
27535846Create StudyMultipoint genome-wide linkage scan for nonword repetition in a multigenerational family further supports chromosome 13q as a locus for verbal trait disorders.Human geneticsTruong DT, Shriberg LD, Smith SD, Chapman KL, Scheer-Cohen AR, Demille MM, Adams AK, Nato AQ, Wijsman EM, Eicher JD, Gruen JRDecember 2016Not Relevant
27178863Create StudyEarly event-related potentials to emotional faces differ for adults with autism spectrum disorder and by serotonin transporter genotype.Clinical neurophysiology : official journal of the International Federation of Clinical NeurophysiologyFaja, Susan; Dawson, Geraldine; Aylward, Elizabeth; Wijsman, Ellen M; Webb, Sara JaneJune 2016Not Determined
27120335Create StudyGenetic Candidate Variants in Two Multigenerational Families with Childhood Apraxia of Speech.PloS onePeter B, Wijsman EM, Nato AQ, Matsushita MM, Chapman KL, Stanaway IB, Wolff J, Oda K, Gabo VB, Raskind WHJanuary 2016Not Determined
26866700Create StudyFamily-based approaches: design, imputation, analysis, and beyond.BMC geneticsWijsman EM2016Not Relevant
26231429Create StudyPBAP: a pipeline for file processing and quality control of pedigree data with dense genetic markers.Bioinformatics (Oxford, England)Nato Jr, Alejandro Q; Chapman, Nicola H; Sohi, Harkirat K; Nguyen, Hiep D; Brkanac, Zoran; Wijsman, Ellen MDecember 1, 2015Not Relevant
26204995Create StudyWhole exome sequencing in extended families with autism spectrum disorder implicates four candidate genes.Human geneticsChapman, Nicola H; Nato Jr, Alejandro Q; Bernier, Raphael; Ankenman, Katy; Sohi, Harkirat; Munson, Jeff; Patowary, Ashok; Archer, Marilyn; Blue, Elizabeth M; Webb, Sara Jane; Coon, Hilary; Raskind, Wendy H; Brkanac, Zoran; Wijsman, Ellen MOctober 2015Not Determined
25640677Create StudyJoint analysis of psychiatric disorders increases accuracy of risk prediction for schizophrenia, bipolar disorder, and major depressive disorder.American journal of human geneticsMaier, Robert; Moser, Gerhard; Chen, Guo-Bo; Ripke, Stephan; Cross-Disorder Working Group of the Psychiatric Genomics Consortium; Coryell, William; Potash, James B; Scheftner, William A; Shi, Jianxin; Weissman, Myrna M; Hultman, Christina M; Landén, Mikael; Levinson, Douglas F; Kendler, Kenneth S; Smoller, Jordan W; Wray, Naomi R; Lee, S HongFebruary 5, 2015Not Relevant
25599223Create StudyPsychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways.Nature neuroscienceNetwork and Pathway Analysis Subgroup of Psychiatric Genomics ConsortiumFebruary 1, 2015Not Determined
25519371Create StudyIdentity-by-descent graphs offer a flexible framework for imputation and both linkage and association analyses.BMC proceedingsBlue, Elizabeth Marchani; Cheung, Charles Yk; Glazner, Christopher G; Conomos, Matthew P; Lewis, Steven M; Sverdlov, Serge; Thornton, Timothy; Wijsman, Ellen M2014Not Determined
25519330Create StudyEstimating and adjusting for ancestry admixture in statistical methods for relatedness inference, heritability estimation, and association testing.BMC proceedingsThornton, Timothy; Conomos, Matthew P; Sverdlov, Serge; Blue, Elizabeth M; Cheung, Charles Yk; Glazner, Christopher G; Lewis, Steven M; Wijsman, Ellen M2014Not Determined
25392729Create StudyThe Autism Simplex Collection: an international, expertly phenotyped autism sample for genetic and phenotypic analyses.Molecular autismBuxbaum JD, Bolshakova N, Brownfeld JM, Anney RJ, Bender P, Bernier R, Cook EH, Coon H, Cuccaro M, Freitag CM, Hallmayer J, Geschwind D, Klauck SM, Nurnberger JI, Oliveira G, Pinto D, Poustka F, Scherer SW, Shih A, Sutcliffe JS, Szatmari P, Vicente AM, Vieland V, Gallagher L2014Not Determined
25363760Create StudySynaptic, transcriptional and chromatin genes disrupted in autism.NatureDe Rubeis, Silvia; He, Xin; Goldberg, Arthur P; Poultney, Christopher S; Samocha, Kaitlin; Cicek, A Erucment; Kou, Yan; Liu, Li; Fromer, Menachem; Walker, Susan; Singh, Tarinder; Klei, Lambertus; Kosmicki, Jack; Shih-Chen, Fu; Aleksic, Branko; Biscaldi, Monica; Bolton, Patrick F; Brownfeld, Jessica M; Cai, Jinlu; Campbell, Nicholas G; Carracedo, Angel; Chahrour, Maria H; Chiocchetti, Andreas G; Coon, Hilary; Crawford, Emily L; Curran, Sarah R; Dawson, Geraldine; Duketis, Eftichia; Fernandez, Bridget A; Gallagher, Louise; Geller, Evan; Guter, Stephen J; Hill, R Sean; Ionita-Laza, Juliana; Jimenz Gonzalez, Patricia; Kilpinen, Helena; Klauck, Sabine M; Kolevzon, Alexander; Lee, Irene; Lei, Irene; Lei, Jing; Lehtimäki, Terho; Lin, Chiao-Feng; Ma'ayan, Avi; Marshall, Christian R; McInnes, Alison L; Neale, Benjamin; Owen, Michael J; Ozaki, Noriio; Parellada, Mara; Parr, Jeremy R; Purcell, Shaun; Puura, Kaija; Rajagopalan, Deepthi; Rehnström, Karola; Reichenberg, Abraham; Sabo, Aniko; Sachse, Michael; Sanders, Stephan J; Schafer, Chad; Schulte-Rüther, Martin; Skuse, David; Stevens, Christine; Szatmari, Peter; Tammimies, Kristiina; Valladares, Otto; Voran, Annette; Li-San, Wang; Weiss, Lauren A; Willsey, A Jeremy; Yu, Timothy W; Yuen, Ryan K C; DDD Study; Homozygosity Mapping Collaborative for Autism; UK10K Consortium; Cook, Edwin H; Freitag, Christine M; Gill, Michael; Hultman, Christina M; Lehner, Thomas; Palotie, Aaarno; Schellenberg, Gerard D; Sklar, Pamela; State, Matthew W; Sutcliffe, James S; Walsh, Christiopher A; Scherer, Stephen W; Zwick, Michael E; Barett, Jeffrey C; Cutler, David J; Roeder, Kathryn; Devlin, Bernie; Daly, Mark J; Buxbaum, Joseph DNovember 13, 2014Not Relevant
25313507Create StudySLC6A3 coding variant Ala559Val found in two autism probands alters dopamine transporter function and trafficking.Translational psychiatryBowton E, Saunders C, Reddy IA, Campbell NG, Hamilton PJ, Henry LK, Coon H, Sakrikar D, Veenstra-VanderWeele JM, Blakely RD, Sutcliffe J, Matthies HJ, Erreger K, Galli A2014Not Determined
25241009Create StudySpatial relative risk patterns of autism spectrum disorders in Utah.Journal of autism and developmental disordersBakian AV, Bilder DA, Coon H, McMahon WMApril 2015Not Determined
25132070Create StudyCombining family- and population-based imputation data for association analysis of rare and common variants in large pedigrees.Genetic epidemiologySaad M, Wijsman EMNovember 2014Not Determined
25112184Create StudyValue of Mendelian laws of segregation in families: data quality control, imputation, and beyond.Genetic epidemiologyBlue EM, Sun L, Tintle NL, Wijsman EMSeptember 2014Not Determined
24958436Create StudyPsychiatric comorbidity and medication use in adults with autism spectrum disorder.Journal of autism and developmental disordersBuck TR, Viskochil J, Farley M, Coon H, Mcmahon WM, Morgan J, Bilder DADecember 2014Not Determined
24837662Create StudyA unified test of linkage analysis and rare-variant association for analysis of pedigree sequence data.Nature biotechnologyHu H, Roach JC, Coon H, Guthery SL, Voelkerding KV, Margraf RL, Durtschi JD, Tavtigian SV, Shankaracharya , Wu W, Scheet P, Wang S, Xing J, Glusman G, Hubley R, Li H, Garg V, Moore B, Hood L, Galas DJ, Srivastava D, Reese MG, Jorde LB, Yandell M, Huff CDJuly 2014Not Determined
24768552Create StudyConvergence of genes and cellular pathways dysregulated in autism spectrum disorders.American journal of human geneticsPinto, Dalila; Delaby, Elsa; Merico, Daniele; Barbosa, Mafalda; Merikangas, Alison; Klei, Lambertus; Thiruvahindrapuram, Bhooma; Xu, Xiao; Ziman, Robert; Wang, Zhuozhi; Vorstman, Jacob A S; Thompson, Ann; Regan, Regina; Pilorge, Marion; Pellecchia, Giovanna; Pagnamenta, Alistair T; Oliveira, Bárbara; Marshall, Christian R; Magalhaes, Tiago R; Lowe, Jennifer K; Howe, Jennifer L; Griswold, Anthony J; Gilbert, John; Duketis, Eftichia; Dombroski, Beth A; De Jonge, Maretha V; Cuccaro, Michael; Crawford, Emily L; Correia, Catarina T; Conroy, Judith; Conceição, Inês C; Chiocchetti, Andreas G; Casey, Jillian P; Cai, Guiqing; Cabrol, Christelle; Bolshakova, Nadia; Bacchelli, Elena; Anney, Richard; Gallinger, Steven; Cotterchio, Michelle; Casey, Graham; Zwaigenbaum, Lonnie; Wittemeyer, Kerstin; Wing, Kirsty; Wallace, Simon; van Engeland, Herman; Tryfon, Ana; Thomson, Susanne; Soorya, Latha; Rogé, Bernadette; Roberts, Wendy; Poustka, Fritz; Mouga, Susana; Minshew, Nancy; McInnes, L Alison; McGrew, Susan G; Lord, Catherine; Leboyer, Marion; Le Couteur, Ann S; Kolevzon, Alexander; Jiménez González, Patricia; Jacob, Suma; Holt, Richard; Guter, Stephen; Green, Jonathan; Green, Andrew; Gillberg, Christopher; Fernandez, Bridget A; Duque, Frederico; Delorme, Richard; Dawson, Geraldine; Chaste, Pauline; Café, Cátia; Brennan, Sean; Bourgeron, Thomas; Bolton, Patrick F; Bölte, Sven; Bernier, Raphael; Baird, Gillian; Bailey, Anthony J; Anagnostou, Evdokia; Almeida, Joana; Wijsman, Ellen M; Vieland, Veronica J; Vicente, Astrid M; Schellenberg, Gerard D; Pericak-Vance, Margaret; Paterson, Andrew D; Parr, Jeremy R; Oliveira, Guiomar; Nurnberger, John I; Monaco, Anthony P; Maestrini, Elena; Klauck, Sabine M; Hakonarson, Hakon; Haines, Jonathan L; Geschwind, Daniel H; Freitag, Christine M; Folstein, Susan E; Ennis, Sean; Coon, Hilary; Battaglia, Agatino; Szatmari, Peter; Sutcliffe, James S; Hallmayer, Joachim; Gill, Michael; Cook, Edwin H; Buxbaum, Joseph D; Devlin, Bernie; Gallagher, Louise; Betancur, Catalina; Scherer, Stephen WMay 1, 2014Not Determined
24718985Create StudyDetection of Mendelian consistent genotyping errors in pedigrees.Genetic epidemiologyCheung CY, Thompson EA, Wijsman EMMay 2014Not Determined
24600472Create StudyA scoring strategy combining statistics and functional genomics supports a possible role for common polygenic variation in autism.Frontiers in geneticsCarayol, Jérôme; Schellenberg, Gerard D; Dombroski, Beth; Amiet, Claire; Génin, Bérengère; Fontaine, Karine; Rousseau, Francis; Vazart, Céline; Cohen, David; Frazier, Thomas W; Hardan, Antonio Y; Dawson, Geraldine; Rio Frio, ThomasJanuary 2014Not Determined
24507777Create StudyA statistical framework to guide sequencing choices in pedigrees.American journal of human geneticsCheung, Charles Y K; Marchani Blue, Elizabeth; Wijsman, Ellen MFebruary 6, 2014Not Determined
24243664Create StudyPower of family-based association designs to detect rare variants in large pedigrees using imputed genotypes.Genetic epidemiologySaad, Mohamad; Wijsman, Ellen MJanuary 2014Not Determined
24167172Create StudyMaternal prenatal weight gain and autism spectrum disorders.PediatricsBilder DA, Bakian AV, Viskochil J, Clark EA, Botts EL, Smith KR, Pimentel R, McMahon WM, Coon HNovember 2013Not Determined
23943636Create StudyDRAW+SneakPeek: analysis workflow and quality metric management for DNA-seq experiments.Bioinformatics (Oxford, England)Lin CF, Valladares O, Childress DM, Klevak E, Geller ET, Hwang YC, Tsai EA, Schellenberg GD, Wang LSOctober 1, 2013Not Determined
23933821Create StudyGenetic relationship between five psychiatric disorders estimated from genome-wide SNPs.Nature geneticsCross-Disorder Group of the Psychiatric Genomics Consortium (see original citation for additional authors)September 2013Not Determined
23593035Create StudyAnalysis of rare, exonic variation amongst subjects with autism spectrum disorders and population controls.PLoS geneticsLiu, Li; Sabo, Aniko; Neale, Benjamin M; Nagaswamy, Uma; Stevens, Christine; Lim, Elaine; Bodea, Corneliu A; Muzny, Donna; Reid, Jeffrey G; Banks, Eric; Coon, Hillary; Depristo, Mark; Dinh, Huyen; Fennel, Tim; Flannick, Jason; Gabriel, Stacey; Garimella, Kiran; Gross, Shannon; Hawes, Alicia; Lewis, Lora; Makarov, Vladimir; Maguire, Jared; Newsham, Irene; Poplin, Ryan; Ripke, Stephan; Shakir, Khalid; Samocha, Kaitlin E; Wu, Yuanqing; Boerwinkle, Eric; Buxbaum, Joseph D; Cook Jr, Edwin H; Devlin, Bernie; Schellenberg, Gerard D; Sutcliffe, James S; Daly, Mark J; Gibbs, Richard A; Roeder, KathrynApril 2013Not Determined
23561844Create StudyGIGI: an approach to effective imputation of dense genotypes on large pedigrees.American journal of human geneticsCheung, Charles Y K; Thompson, Elizabeth A; Wijsman, Ellen MApril 4, 2013Not Determined
23453885Create StudyIdentification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis.Lancet (London, England)Cross-Disorder Group of the Psychiatric Genomics ConsortiumApril 20, 2013Not Determined
23259942Create StudyThe autism sequencing consortium: large-scale, high-throughput sequencing in autism spectrum disorders.NeuronBuxbaum, Joseph D; Daly, Mark J; Devlin, Bernie; Lehner, Thomas; Roeder, Kathryn; State, Matthew W; Autism Sequencing ConsortiumDecember 20, 2012Not Determined
23008058Create StudyExcess mortality and causes of death in autism spectrum disorders: a follow up of the 1980s Utah/UCLA autism epidemiologic study.Journal of autism and developmental disordersBilder D, Botts EL, Smith KR, Pimentel R, Farley M, Viskochil J, McMahon WM, Block H, Ritvo E, Ritvo RA, Coon HMay 2013Not Determined
22843504Create StudyIndividual common variants exert weak effects on the risk for autism spectrum disorders.Human molecular geneticsAnney, Richard; Klei, Lambertus; Pinto, Dalila; Almeida, Joana; Bacchelli, Elena; Baird, Gillian; Bolshakova, Nadia; Bölte, Sven; Bolton, Patrick F; Bourgeron, Thomas; Brennan, Sean; Brian, Jessica; Casey, Jillian; Conroy, Judith; Correia, Catarina; Corsello, Christina; Crawford, Emily L; de Jonge, Maretha; Delorme, Richard; Duketis, Eftichia; Duque, Frederico; Estes, Annette; Farrar, Penny; Fernandez, Bridget A; Folstein, Susan E; Fombonne, Eric; Gilbert, John; Gillberg, Christopher; Glessner, Joseph T; Green, Andrew; Green, Jonathan; Guter, Stephen J; Heron, Elizabeth A; Holt, Richard; Howe, Jennifer L; Hughes, Gillian; Hus, Vanessa; Igliozzi, Roberta; Jacob, Suma; Kenny, Graham P; Kim, Cecilia; Kolevzon, Alexander; Kustanovich, Vlad; Lajonchere, Clara M; Lamb, Janine A; Law-Smith, Miriam; Leboyer, Marion; Le Couteur, Ann; Leventhal, Bennett L; Liu, Xiao-Qing; Lombard, Frances; Lord, Catherine; Lotspeich, Linda; Lund, Sabata C; Magalhaes, Tiago R; Mantoulan, Carine; McDougle, Christopher J; Melhem, Nadine M; Merikangas, Alison; Minshew, Nancy J; Mirza, Ghazala K; Munson, Jeff; Noakes, Carolyn; Nygren, Gudrun; Papanikolaou, Katerina; Pagnamenta, Alistair T; Parrini, Barbara; Paton, Tara; Pickles, Andrew; Posey, David J; Poustka, Fritz; Ragoussis, Jiannis; Regan, Regina; Roberts, Wendy; Roeder, Kathryn; Roge, Bernadette; Rutter, Michael L; Schlitt, Sabine; Shah, Naisha; Sheffield, Val C; Soorya, Latha; Sousa, Inês; Stoppioni, Vera; Sykes, Nuala; Tancredi, Raffaella; Thompson, Ann P; Thomson, Susanne; Tryfon, Ana; Tsiantis, John; Van Engeland, Herman; Vincent, John B; Volkmar, Fred; Vorstman, J A S; Wallace, Simon; Wing, Kirsty; Wittemeyer, Kerstin; Wood, Shawn; Zurawiecki, Danielle; Zwaigenbaum, Lonnie; Bailey, Anthony J; Battaglia, Agatino; Cantor, Rita M; Coon, Hilary; Cuccaro, Michael L; Dawson, Geraldine; Ennis, Sean; Freitag, Christine M; Geschwind, Daniel H; Haines, Jonathan L; Klauck, Sabine M; McMahon, William M; Maestrini, Elena; Miller, Judith; Monaco, Anthony P; Nelson, Stanley F; Nurnberger Jr, John I; Oliveira, Guiomar; Parr, Jeremy R; Pericak-Vance, Margaret A; Piven, Joseph; Schellenberg, Gerard D; Scherer, Stephen W; Vicente, Astrid M; Wassink, Thomas H; Wijsman, Ellen M; Betancur, Catalina; Buxbaum, Joseph D; Cook, Edwin H; Gallagher, Louise; Gill, Michael; Hallmayer, Joachim; Paterson, Andrew D; Sutcliffe, James S; Szatmari, Peter; Vieland, Veronica J; Hakonarson, Hakon; Devlin, BernieNovember 1, 2012Not Determined

Relevant Publications
PubMed IDStudyTitleJournalAuthorsDate
27956748Create StudyAssociation of rare missense variants in the second intracellular loop of NaV1.7 sodium channels with familial autism.Molecular psychiatryRubinstein, M; Patowary, A; Stanaway, I B; McCord, E; Nesbitt, R R; Archer, M; Scheuer, T; Nickerson, D; Raskind, W H; Wijsman, E M; Bernier, R; Catterall, W A; Brkanac, ZFebruary 1, 2018

You can use "Add New Data Expected" to add exsiting structures and create your project's list. However, this is also the method you can use to request new structures be created for your project. When adding the Data Expected item, if the structure already exists you can locate it and specify your dates and enrollment. To add a new structure and request it be defined in the Data Dictionary, select Upload Definition and attach the definition or material needed to create it, including manual, codebooks, forms, etc. If you have multiple files, please upload a zipped archive containing them all.

Expected dates should be selected based on the standard Data Sharing Regimen and are restricted to within date ranges based on the project start and end dates.

Data Expected
Data ExpectedTargeted EnrollmentInitial SubmissionSubjects SharedStatus
Mullen Scales of Early Learning info icon
4207/15/2013
42
Approved
Genomics/omics info icon
80307/15/2013
803
Approved
ABC Community info icon
69307/15/2013
693
Approved
Leiter International Performance Scale-Revised (Leiter-R) info icon
807/15/2013
8
Approved
ADOS info icon
84807/15/2013
848
Approved
ADI-R info icon
43007/15/2013
430
Approved
Social Responsiveness Scale (SRS) info icon
1,60107/15/2013
1,601
Approved
Wechsler Abbreviated Scale of Intelligence (WASI) info icon
66007/15/2013
660
Approved
Comprehensive Test of Phonological Processing (CTOPP) info icon
1,09007/15/2013
1,090
Approved
Social Communication Questionnaire (SCQ) info icon
58107/15/2013
581
Approved
Broad Autism Phenotype Questionnaire (BAPQ) info icon
48207/15/2013
482
Approved
Behavior Assessment System for Children (BASC) info icon
46607/15/2013
466
Approved
Developmental Behavior Checklist info icon
19507/15/2013
195
Approved
Expanded Token Test info icon
69607/15/2013
696
Approved
Wechsler Intelligence Scale for Children info icon
16607/15/2013
166
Approved
DAS-II: Differential Ability Scales info icon
17507/15/2013
175
Approved
Peabody Picture Vocabulary Test, Fourth Edition info icon
52607/15/2013
526
Approved
Wechsler Adult Intelligence Scale info icon
44407/15/2013
444
Approved
Repetitive Behavior Scale - Revised (RBS-R) info icon
22407/15/2013
224
Approved
Stanford Binet info icon
4307/15/2013
43
Approved
Physical Exam info icon
1,96207/15/2013
1,962
Approved
Research Subject and Pedigree info icon
1,68907/15/2013
1,689
Approved
Child Anxiety and Depression Scale - Parent (RCAD-P) info icon
44307/15/2013
443
Approved
Clinical Evaluation of Language Fundamentals (CELF) info icon
57107/15/2013
571
Approved
Vineland (Parent and Caregiver) info icon
60307/15/2013
603
Approved
Structure not yet defined

Collection Owners and those with Collection Administrator permission, may edit a collection. The following is currently available for Edit on this page:

Associated Studies

Studies that have been defined using data from a Collection are important criteria to determine the value of data shared. The number of subjects column displays the counts from this Collection that are included in a Study, out of the total number of subjects in that study. The Data Use column represents whether or not the study is a primary analysis of the data or a secondary analysis. State indicates whether the study is private or shared with the research community.

Study NameAbstractCollection/Study SubjectsData UsageState
Examining the validity of the use of ratio IQs in psychological assessments IQ tests are amongst the most used psychological assessments, both in research and clinical settings. For participants who cannot complete IQ tests normed for their age, ratio IQ scores (RIQ) are routinely computed and used as a proxy of IQ, especially in large research databases to avoid missing data points. However, because it has never been scientifically validated, this practice is questionable. In the era of big data, it is important to examine the validity of this widely used practice. In this paper, we use the case of autism to examine the differences between standard full-scale IQ (FSIQ) and RIQ. Data was extracted from four databases in which ages, FSIQ scores and subtests raw scores were available for autistic participants between 2 and 17 years old. The IQ tests included were the MSEL (N=12033), DAS-II early years (N=1270), DAS-II school age (N=2848), WISC-IV (N=471) and WISC-V (N=129). RIQs were computed for each participant as well as the discrepancy (DSC) between RIQ and FSIQ. We performed two linear regressions to respectively assess the effect of FSIQ and of age on the DSC for each IQ test, followed by additional analyses comparing age subgroups as well as FSIQ subgroups on DSC. Participants at the extremes of the FSIQ distribution tended to have a greater DSC than participants with average FSIQ. Furthermore, age significantly predicted the DSC, with RIQ superior to FSIQ for younger participants while the opposite was found for older participants. These results question the validity of this widely used alternative scoring method, especially for individuals at the extremes of the normal distribution, with whom RIQs are most often employed.217/17423Secondary AnalysisPrivate
Controls for SCCRIPTo establish a well characterized cohort for pediatric patients living with sickle cell disease114/11185Secondary AnalysisPrivate
Working Title: Differentiating Core Autism SymptomatologyAutism spectrum disorder (ASD) is characterized by persistent deficits in social communication and social interaction, social-emotional reciprocity, and repetitive behavior or restricted interest (American Psychiatric Association [APA], 2013). This study extends the existing literature by clarifying the extent to which mental health disorder symptoms differentially converge with autism symptoms related to social communication and restricted and repetitive behavior, as well as the extent to which mental health symptoms are empirically differentiated from the core autism symptom domains. Although there is a well-documented correlation between the severity of core ASD symptoms and the presence of mental health disorder symptoms, such as anxiety and irritability, the nature of this linkage remains poorly understood. In this project, the National Database for Autism Research (NDAR) and Research Domain Criteria Database (RDoCdb) were used to observe continuous symptom measures such as the Social Responsiveness Scale (SRS) and the Child Behavior Checklist (CBCL) to examine correlation matrices as well as factor structure models to examine these patterns of association. The SRS “social communication” and “repetitive restricted” subscales were correlated with the CBCL externalizing, internalizing, attention, conduct, aggression, psychosomatic, and withdrawn subscales. We hypothesized that “repetitive and restricted” behaviors would be more correlated with the CBCL scales than would the “social communication” scale. These results were also interpreted according to age and IQ. In conclusion, this study may elucidate ongoing questions about the centrality of mental health symptoms like anxiety to aspects of ASD taxonomy. 1518/11144Secondary AnalysisPrivate
The effect of compensatory mechanisms during and after pregnancy on a child's developmentEarly childhood involves rapid processes of human growth leading to different trajectories in physical, cognitive, social, and emotional development (Graignic-Philippe et al., 2014). These processes are influenced by a wide variety of factors such as maternal health, environmental stressors, and early childhood experiences. Current literature has shown how exposure to both acute and chronic stress during pregnancy have a pathogenetic effect throughout childhood (Kim & Leventhal, 2015; Rice, et al, 2010), leading to neurotypical or atypical development. Studies have shown how these stressors are linked neurodevelopmental disorders such Autism Spectrum Disorders (Zerbo et al., 2015; Atladóttir et al., 2012) or Attention Deficit Hyperactivity Disorder (Rosenqvist et al., 2019). In recent years, there has been a shift from traditional diagnostic research models to synthesis of different scientific fields to map lifecourse development in order for rapid translation into healthcare practices (Halfon et al., 2014). Whilst there are studies showing links between stress and atypical developmental outcomes, there is still very limited literature on compensatory mechanisms found pre- and post-pregnancy, which illustrate development of protective factors (such as presence of self-regulation, high verbal intelligence, sociability, adept social communication) against atypical developmental outcomes. This study aims to identify and measure the presence of these protective factors that appear to guard against or mitigate the emergence of neurodevelopmental disorders. Therefore, nationwide and longitudinal data are needed in order to accurately create risk models in order to map developmental trajectories. 131/5717Secondary AnalysisPrivate
Autism Sensory Research Consortium Cross-lab Integrative Data Analysis Since 2013, when sensory features were officially added to the diagnostic criteria for autism, research into the sensory manifestations of the condition has increased dramatically. However, the majority of this research has primarily been conducted using small laboratory-based samples of children on the autism spectrum, substantially limiting the hypotheses that can be tested in any one dataset and the generalizability of results to the wider autistic population. The Autism Sensory Research Consortium (ASRC), funded by the Nancy Lurie Marks Family Foundation, represents the first major international collaboration of over a dozen research groups that study sensory functioning in autism. As a major thrust of this collaboration, the ASRC has begun a data sharing initiative, in which all participating labs can contribute existing data from their past and present research studies to a centralized database. These “Big Data” can then be systematically examined using powerful large-sample statistical techniques such as structural equation modeling and item response theory, which will allow researchers to test more complex hypotheses regarding the nature of sensory differences in autism and their relationships with sociodemographic and non-sensory clinical features. Once data from all sites has been pooled, it will be analyzed using a method called integrative data analysis, which is specially designed to derive insights from large and heterogeneous samples. One major advantage of this methodology is the ability to construct and test measurement models of sensory symptoms, determining the most appropriate set of questions for assessing each construct and making sure that the scales do not produce biased comparisons when they are examined across diagnostic groups or subsets of the autistic population. Furthermore, measurement models can be constructed to bridge multiple questionnaires, allowing for the calculation of robust composite scores that can be compared between studies that only administered items from one of the contributing questionnaires. These models can further facilitate pooling of data across studies, allowing us to amass even larger datasets to answer questions about sensory function in the autistic population. Furthermore, moving forward, the composite sensory measures from the integrative data analysis can be employed in other studies, providing investigators in sensory autism research with a suite of reliable and valid behavioral measures that can be used as outcomes in trials of interventions targeting these symptoms. In the long term, this project has the potential to help us better understand the nature of sensory function in persons on the spectrum, as well as how sensory alterations relate to broader features of the condition—specifically, for whom and/or at what point in development sensory features are most predictive of core autism behaviors or other meaningful clinical outcomes such as language acquisition and adaptive behavior. Incorporation of neuroscientific data collected within the ASRC can also possibly shed some light on the neural basis of sensory disruptions in the autistic population. All of this will help to lay a foundation for future work testing the efficacy of candidate interventions aimed at improving sensory function and more distal skills in autistic individuals.4/2110Secondary AnalysisPrivate
Unravelling the Collective Diagnostic Power Behind the Features in the Autism Diagnostic Observation ScheduleBackground: Autism is a group of heterogeneous disorders defined by deficits in social interaction and communication. Typically, diagnosis depends on the results of a behavioural examination called the Autism Diagnostic Observation Schedule (ADOS). Unfortunately, administration of the ADOS exam is time-consuming and requires a significant amount of expert intervention, leading to delays in diagnosis and access to early intervention programs. The diagnostic power of each feature in the ADOS exam is currently unknown. Our hypothesis is that certain features could be removed from the exam without a significant reduction in diagnostic accuracy, sensitivity or specificity. Objective: Determine the smallest subset of predictive features in ADOS module-1 (an exam variant for patients with minimal verbal skills). Methodology: ADOS module-1 datasets were acquired from the Autism Genetic Resource Exchange and the National Database for Autism Research. The datasets contained 2572 samples with the following labels: autism (1763), autism spectrum (513), and non-autism (296). The datasets were used as input to 4 different cost-sensitive classifiers in Weka (functional trees, LADTree, logistic model trees, and PART). For each classifier, a 10-fold cross validation was preformed and the number of predictive features, accuracy, sensitivity, and specificity was recorded. Results & Conclusion: Each classifier resulted in a reduction of the number of ADOS features required for autism diagnosis. The LADtree classifier was able to obtain the largest reduction, utilizing only 10 of 29 ADOS module-1 features (96.8% accuracy, 96.9% sensitivity, and 95.9% specificity). Overall, these results are a step towards a more efficient behavioural exam for autism diagnosis. 147/1832Secondary AnalysisShared
Automated Autism Diagnosis using Phenotypic and Genotypic Attributes: Phase IThe ultimate goal of this project is to develop a predictive system that can automate the diagnosis process for autism using phenotypic and genotypic attributes for classification. At this time, only a first phase is being pursued: starting with scores from Autism Diagnostic Observation Schedule (ADOS) reports, use data-mining techniques to select the smallest set of the most informative evaluation points that can lead to similar behavioral diagnoses as using all report features. The effort began in March, 2016 after data access to NDAR was granted. This report describes the results from that date through the end of December 2016.84/1045Secondary AnalysisPrivate
Brain-based sex differences in autism spectrum disorder across the lifespan: A systematic review of structural MRI, fMRI, and DTI findingsFemales with autism spectrum disorder (ASD) have been long overlooked in neuroscience research, but emerging evidence suggests they show distinct phenotypic trajectories and age-related brain differences. Sex-related biological factors (e.g., hormones, genes) may play a role in ASD etiology and have been shown to influence neurodevelopmental trajectories. Thus, a lifespan approach is warranted to understand brain-based sex differences in ASD. This systematic review on MRI-based sex differences in ASD was conducted to elucidate variations across the lifespan and inform biomarker discovery of ASD in females. We identified articles through two database searches. Fifty studies met criteria and underwent integrative review. We found that regions expressing replicable sex-by-diagnosis differences across studies overlapped with regions showing sex differences in neurotypical (NT) cohorts, in particular regions showing NT male>female volumes. Furthermore, studies investigating age-related brain differences across a broad age-span suggest distinct neurodevelopmental patterns in females with ASD. Qualitative comparison across youth and adult studies also supported this hypothesis. However, many studies collapsed across age, which may mask differences. Furthermore, accumulating evidence supports the female protective effect in ASD, although only one study examined brain circuits implicated in “protection.” When synthesized with the broader literature, brain-based sex differences in ASD may come from various sources, including genetic and endocrine processes involved in brain “masculinization” and “feminization” across early development, puberty, and other lifespan windows of hormonal transition. Furthermore, sex-related biology may interact with peripheral processes, in particular the stress axis and brain arousal system, to produce distinct neurodevelopmental patterns in males and females with ASD. Future research on neuroimaging-based sex differences in ASD would benefit from a lifespan approach in well-controlled and multivariate studies. Possible relationships between behavior, sex hormones, and brain development in ASD remain largely unexamined.161/759Secondary AnalysisShared
Can we improve the precision of the ADOS? An application of Item Response TheoryThe current study examined the measurement precision of the Autism Diagnostic Observation Schedule (ADOS) across the continuum of severity of autism spectrum disorder (ASD) traits. Modules 3 and 4 of the ADOS assess two domains of ASD (Social Affect and Restrictive and Repetitive Behaviors (RRB)) among verbally fluent adolescents and adults. Currently, scores for these two domains are produced using only a subset of the administered items. Given prior findings demonstrating the poor reliability of the RRB domain, this study examined whether measurement precision of the ASD domains measured by ADOS can be improved by incorporating items that are collected but not scored in the current diagnostic algorithm. Measurement precision is estimated using item response theory (IRT) models, which allows for an examination of reliability across a continuum of ASD domain severity. Results suggest that although the ADOS Module 3 and 4 measuring Social Affect are already very reliable near mean levels of the trait, adding additional items can improve the reliability of scores at moderately low and moderately high levels of Social Affect. However, even with additional items, the ADOS Modules 3 and 4 do not allow for reliable measurement of RRB with adolescents and young adults. 130/423Secondary AnalysisPrivate
Identifying Sex-Specific Cognitive and Diagnostic Profiles for Children on the Autism Spectrum81/252Secondary AnalysisPrivate
* Data not on individual level
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